SpaceX and Cursor team up to topple Claude Code | E2279

If you like the AI coding tools you have today, you're going to like them a whole lot more down the road. As well as being hyper competitive, BitTensor is also extremely cooperative. How much money do you need to raise to put together a compelling subnet pitch pre-launch? It's less about the amount as a fixed total. It's more about validation. You might be an amazing ML engineer. You might be an incredible full stack dev, but BitTensor is adversarial and the miners are like very, very intense. They're going to tear you apart. You could get wiped out and lose your initial capital. This race is going to yield a lot of steel on steel sharpening, as we say. We actually have some news that we want to break right here on This Week in Startups with you guys. All right. This Week in Startups is brought to you by Notion. Bring all your notes, docs, and projects into one space that just works with AI built right in. Try Notion with Notion Agent at notion.com slash twist. Grasshopper Bank. Time is money. Don't waste either. Go to grasshopper.bank slash twist and get an exclusive $500 cash bonus just for opening an account. And LinkedIn Jobs. Hire right the first time. Post your first job and get $100 off towards your job post at linkedin.com slash twist. Hello and welcome back to Twist. My name is Alex. I'm joined today by my dear friend, Lon Harris. Lon, how are you? Doing great. Happy to be here. All right. April 22nd, 2026, or as we say here at Twist, AO86. That's how many days it's been. That's what we say when we remember to say. We're almost at the exact three-month open claw point, and I feel like open claw mania is dying down. That's how I feel. Dying down a little bit. Hermes agent is doing quite well. People are talking about co-work. But I will say, and we're going to get to this at the end of the show, there are some really awesome open weight models that have come out that are incredibly price and intelligence efficient long. So people might want to take a second look at OpenClaw. But on the show today, we're talking SpaceX and Cursor, the biggest deal in the news in the last six months, I want to say. And then we have a couple of folks from the realm of BitTensor. We have the folks from BitStarter, and then we're going to talk to the people behind Subnet 11. That's Ning Ren. It's going to be an absolute bop. But Lon, break down for us the headlines here of the big XAI SpaceX news. Well, I think first we should give a shout out to our good friends at Plot. I don't have my Plot pin. It's the first time I've made it on the show. I feel naked. My Plot pin is over there on the desk, and I'm not going to interrupt the show to go right over to get it. But Plot, folks, incredible technology. We all have a Note pin. I have the Note S pin. And what's so amazing about it is that it works in the background. You just hit the button. It starts recording. It puts a little light on so everybody around you can see you're recording. It's not this is not a spy camera technology. And it not only records notes from you while you're going about your day, bits of the conversation, whoever you're talking to, but it sort of organizes them thoughtfully. It's got that AI powered brain. So it's not just you're transcribing everything you hear in a big block of text. It's giving you the context, everything you need to go back, search through what was being said, find the nugget of information that you need. It's really like having a, you know, second brain that you can store things in if you are a little forgetful like myself. Yeah, it's incredible for me to not forget things. Also, mine is currently charging because I use it all the time. I forgot to take it off the charger and put it back on for the show. That's the message you should take. We're both using our plod pins so much that we're having trouble getting them together for the show because they're in use currently, folks. And they actually have a really great battery life. So I think this is more just you and I being disorganized. But if you want to get your own Plod, NotePinS, you can go to plod.ai, P-L-A-U-D, dot AI slash twist. Use the code twist to save 10%. Stop forgetting things. Take excellent notes. Put AI to work for you. Plod, we love them. Thanks, guys, for sponsoring the show. As J. Cal says, we applaud Plod. Back to the news. SpaceX. SpaceX. Yes. So the big news yesterday, everybody freaked out in the afternoon. It was like right after we recorded another show, and it was like, ah! So we'll talk about it now. SpaceX and Cursor are partnering on AI models. Of course, Cursor, the popular AI coding model and harness company, they're going to work together to create, and I quote, the world's best coding and knowledge work AI as a team, or as Cursor put it, we're partnering with SpaceX to improve Composer. So the idea is that it's sort of a collaboration, but it's also sort of an early announcement of a potential acquisition. SpaceX is going to either pay Cursor $10 billion for this model collaboration that they're working on, or they're going to, at the end of designing this model, just buy Cursor out for $60 billion by the end of 2026 at some point. So it's an interesting, like the original announcements were all like, SpaceX buying Cursor. And like, maybe at one point, they're sort of trial running it for the next few months. So why does this deal make sense from a headline perspective? It's pretty simple. Cursor has done a very good job competing with Codex from OpenAI and also CloudCode from Anthropic. As those two coding products long have become really the de facto of the industry, Cursor has continued to grow. It's reached, I think, $2 billion in annualized run rate as of earlier this year. A very impressive number. And I would say most critically, they released Composer 2, which is their latest model that they built for themselves. It was announced a couple weeks back, and it does seem to perform quite well against industry standard benchmarks, i.e. it's competitive with the models from the best companies. All right, so why does that matter if you're XAI, which is now part of SpaceX? Well, XAI had a really big hit coding model called Grok Code Fast 1. Right. It was incredibly cheap. It was incredibly quick. Everyone used it. It took over Open Router for a while. But since then, the company has not been at the tip of the spear, as we might say, in the AI coding game. So what does XAI have? A lot of compute. What does Cursor have? A model that's quite good and the chops to make more. You put the two together, you take XAI's GPU clusters and Composer's AI model making skills. And in theory, Lon, it's a match made in heaven. Well, I mean, we've seen so much discussion just in the last few weeks. There's more in the docket about this, about how every one of these companies now feels like they need their own AI coding product that's locked in, that's best in class. Like that's what's driving so much of this industry. Everybody, again, as you said, trying to compete with the Claude codes of the world, the codexes of the world. We had that Google all hands red alert from Sergey Brin the other day. He's basically saying the same thing, like, where are we? Why isn't Gemini best of class and the thing every developer is using? So I think it's interesting sort of looking at it from outside that that particular tool, that that form function of the AI coding assistant has become essentially what's driving the entire AI industry at this point. Absolutely. Here is the benchmarks that Cursor put up when they put out Composer 2. their recent model. And as you can see, if you're on the audio version, it's basically a little bit behind GPT 5.4, but it's ahead of Opus 4.6, 4.5, and Composer 1.5, of course, the preceding generation. This was not updated for 4.7, though. How dare they? No, no, it's not. It's not our fault that Anthropic's been cooking quite a lot in Cursors. Those teens in Discord who are already using Mythos, I hope they can tell us how that stacks up. I don't know if you followed that, sir. Oh, yeah, we'll get through that. But the other thing that's really important here is that Cursor has a lot of developer market share. Yes. And what that unlocks for the company is a lot of information about how people are using its models in a production environment. You can learn from the logs, the traces, call it what you will. There is an opt-out built into how Cursor functions long. So you can't just expect them to have every piece of data from every single user or customer, but probably there's enough people opting in to share that they have a pretty good corpus of information on a day-to-day basis. So XAI doesn't have that because their coding models have not been as well received as those from other companies. So data and models from Cursor and then a lot of compute from XAI, SpaceX. I think that there's two prices here that are different. So the $10 billion number is very expensive. Like to partner with a company to work on some stuff. For a single product. If you're like, we got this new model out of it. We really love it. Like 10 peanuts is a big number. Yeah. 10 peanuts is a big number, and we don't know exactly how costs will be shared. You know, is Cursor going to pay for some of the power bill over at XAI's Colossus, you know, supercomputers or not? But $60 billion is not a large number because, as we've seen recently, Cursor is considering raising capital today at a $50 billion payment. Right. And so, exactly to the end of the year, presumably you would be well above the $60 billion. So, theoretically, SpaceX could be getting a little bit of a discount on that by where we expect Cursor to be in December. Absolutely. So it's kind of a call option on buying Cursor. It's a big old call option. So the risk that I would say SpaceX slash XAA are taking is what if this partnership doesn't bear the fruit they're hoping it does and they're still on the hook for $10 billion? Right. I did have one other financial question. And I look to you, Alex, as somebody who's a little bit smarter about this than me. We also have been hearing a whole lot about a SpaceX IPO in the imminent future. Is there a chance that this is narrative in some way, that this is part of the storytelling as we go into the IPO? like look at these massive deals. Maybe if you were a little skeptical about XAI because of the model situation, well, now you have this very reassuring news that they're going to be teaming with one of the leaders in that space and so forth. Yeah. Hiring can be its own full-time job. And hey, guess what? I already have a full-time job. I make podcasts and I invest. But when you're running a small company, we both know every hire matters. You don't want to waste any of the seats you have at your company. And the best partner you can have is LinkedIn Hiring Pro. Why? There's a billion people using LinkedIn. All the great talent are there. If you're proud of your work, you build a LinkedIn page and you update it. LinkedIn Hiring Pro is going to streamline and simplify the entire process for you. Nearly 60% of companies using LinkedIn Hiring Pro. You're going to get an incredible candidate to interview in the first week. And, you know, we're looking for a new producer for the pod. We did shout outs here on the show. We posted it on my social media. We asked friends, you know, where we found our next great hire LinkedIn. And it was competitive. We had like three or four really good choices. So hire right the first time, post your first job and get a hundred dollars off towards your post at linkedin.com slash hiring pro offer. That's linkedin.com slash hiring pro offer terms and conditions apply. So SpaceX going public by itself is a two-part business. It's a launch company and it's also a satellite internet company. And the latter half of that's been very, very profitable for SpaceX based on what we've done. AI and X, I mean, that's also sort of part and part. And then you have the other two things, XAI and X. As you said, X, let's just go ahead and say it's breakeven, probably somewhere in and around that, or the losses or profits from it are not really material compared to the scale of Space Launch, Starlink, and XAI. But the problem is XAI brings a lot of costs with it. It brings, I think, a little bit of debt. It spends a lot of money on GPUs. It is not cheap to build, essentially overnight, one of the world's largest compute clusters. So if you're an investor looking at this kind of Elon conglomerate, if you will, there are some clear financial winners today. And there are some bets that may pay off later on, but you're going to pay for those bets now. So I think you're dead on. This is a way to change the narrative a little bit. XAI is not merely the third or fourth place company in the current AI model game. It is now the partner and potential owner of Cursor, a multi-billion dollar revenue company that has a lot more developer mind share. So it does, I think, ameliorate some concerns, but it's doing so at the cost of 10 or 60 billion dollars. And we don't know long today if those sums are predicated on cash, stock or a mix, because it could either be debt you have to raise, cash you have to burn or shares you have to issue or a combination. As is so often in the AI industry, it's sort of purely theoretical at this point. We could talk about it. It's on paper. But it's not really anything concrete that we can sort of look at the numbers and break down at this point. It's a promise. I also – it is a promise. But I do think that when you're thinking about the size of the prize, it's worth taking some expensive swings. And so the reason why I'm not shouting about the $10 billion fee, essentially, is because I do think that if you get very good at creating AI models that can do coding, you're much closer to recursive self-improvement, which is when an AI model can work on itself and improve itself. So right now, I think we consider the cursors and the cloud codes of the world as individual accelerants for developers and development teams. But if you want to build the AI model that can improve itself long term, you're going to need to have at a minimum state of the art coding shops, if not the market leading option. And XAI just isn't there. So a way to trim the page. It's that flywheel. It's that the more developers that are using it to code, the more data you're getting about good coding, the better the model becomes. And so as we look to potentially AGI or models that can write brilliant, beautiful code without a human in the loop ever, whoever has the most data theoretically wins. And then there's the future component to this. Here's a tweet from Jason, who is out today. He'll be back later on. Don't worry. He's not off the show, just off for today. We kicked him off. He said, I mean, everyone gets a day after that. Hostile takeover, folks. Hostile takeover. So Jason says, fire emoji wow. Very strategic and bold move. Colossus, which is the XAI supercomputer, is a super weapon for SpaceX already. Can you imagine when it scales to the stars? Right. So the other part of this is, let's say you do get, let's just say XAI buys Cursor. SpaceX buys Cursor. The experiment works out. They take all that data and learning and model prowess, and they make something fantastic. Okay, then what? Right now, XAI has, I think, the only example of compute glut in the AI game. But if they make a model that is as good as they hope, that's going to become a compute shortage overnight. As everybody switches over from the clods of the world to the groks of the world, and then all of a sudden they're at the center of everything. But today, Anthropic is throttling, blocking, turning people off, trying to just keep itself online. GitHub co-pilot stops signing up new individual paid accounts to hold back compute. Everyone's struggling. I'm not even doing code. I'm like doing tweets and Claude is like, hang on, brother. I need a break. Give me 45 minutes. And I'm not taking apart our back end or anything. But if you do believe that SpaceX has a chance at building orbital data centers, which we've talked about the star cloud which was 500 company then you can kind of sketch out a future in which they have the best coding model and the most compute right which is a lot a lot of clearly that's elon's vision as we become a you know i forget what the what the russian name is like as we pursue becoming a various higher level civilization and powering our data centers directly from the sun obviously we would need to have the best compute and the best models in space We're trying to become a Kardashev level two civilization. And if you don't know what that means, you are not spending enough time reading science fiction. Fix that. This is a dataset from Open Router. And what it shows is the most popular coding models. I think this is the last week, maybe the last day. But Lon, if you take a look at this, you see some open models from folks like Moonshot, which is Chinese, Minimax, Chinese, Step1, Chinese, NVIDIA, Anthropic, OpenAI, and that's it. And so I think that this is probably the fire they're trying to put out. They have to get back on this board. They have to become competitive. And so maybe a $10 billion bet for a company that's supposed to be worth $1.25 trillion is, and this is an odd thing to say, it's pocket change. It's not that much money in that context. It's three MLB teams, I guess, given the recent sale price. It's still a lot of money. But yes, in perspective of what these companies are doing, it might make more sense. Well, no matter what, I think the takeaway for folks out there is that if you like the AI coding tools you have today, you're going to like them a whole lot more down the road because Lord above, there is more improvement coming. This race is going to yield a lot of steel on steel sharpening, as we say. And I think it's going to turn everyone into, I mean, just superhuman developers. I can't wait. We're already seeing it. I mean, these products are coming out at an insane, insanely rapid rate. Open Claw, I feel like, is updated every other day. There's a new version. So, yeah, like the drive to become the new Claude Code is massive and incredibly intense. As intense as any race I think we've seen in tech since I've been following it. In fact, you know, Lon, why don't we talk to a couple of folks from the world of BitTensor and see what AI coding model and harness they are using. I would love to do that. So I want to bring up here to the stage our dear friends Chris Zakaria and Brian McRindle from BitStarter. And they are in the Gen Z Hype House podcast studio with mood lighting. Boys, welcome to the show. Look at that. Thank you very much. Great to be here. Yeah, doesn't it look beautiful? It does. What does orange lighting signify? What mood is that? Our logo is orange. So actually, it looks like we set it up this way. But that was pure choice. Completely planned. Yeah, I feel like it's calming. It's giving me a calming, soothing vibe. I was getting Halloween vibes. But listen guys before we get into what Bitstarter does, I'm curious for your own development work for the company, what are you guys using these days? You mean in terms of AI tools? Yeah. Opus 4.7, tooled up to the max, code and co-work 24-7. They token maxing Alex I like consistently on three instances of Code and Composer and like making them fight against each other Wow Oh wow Yeah. So what would it take for you guys to swap out your Anthropic and Composer models for something from XAI? Like how much better would they have to get this starting story of the show? Oh, well, Brian's the founding engineer. So I think that's one for you. Yeah, honestly, for me, it's always just like ease of use in the sense of like whatever. One of the most valuable things is not impeding someone's workflow. Like I wouldn't want to go have to download another tool that's not cleave based or something that's, you know, isn't clearly better. Like there's a bunch of people who are like at the edge of everything and they want to use absolutely every single tool, but that's not the vast majority of engineers, right? It just needs to be known to be the best. I need to see it on the leaderboards. I need to see it on places like Arena. If you guys know where Arena, LM Arena. Oh yeah. It just needs to be like, I think there was a whole push for cloud code. And it was very clear that it was the best. And then I moved over and said, yep, that's obvious. I have some arena data here for anyone curious. So this is a rundown of the leading AI labs in the coding context grouped. And so the current leaderboard is Anthropic. Then Z.ai, the Chinese company behind the really solid GLM 5.1 model. Alibaba with the Quinn family. OpenAI, of course, GPT 5.4, Codex, Google, Moonshot, Xiaomi, Minimax, then XAI, then DeepSeek. That's the top 10 in the world today. That's kind of a shocking list. A lot of Chinese companies, they're doing quite well. I'm encouraged by that. But guys, let's talk about Bitstarter. So we have been going deep in the world of BitTensor. I have talked to so many subnets. We've learned so much. And it's been an absolute treat to see how the economics function. but you guys have put together kind of an on-ramp, if you will, to BitTensor via Bitstarter, which you guys kind of called the Kickstarter program. So what we want to know is, why couldn't we use Kickstarter for this? Why do we? Yeah. Is there something in the Kickstarter rules that's like no subnets? Here's a startup truth bomb. A lot of founders have no idea what's actually going on with their money. If that's true of your company, hey, no judgments. I know you're busy hiring, building your product, go-to market, all that important stuff. But your company needs a reliable financial partner, not a lifestyle brand, okay? Grasshopper is a real federally-chartered digital bank that's not trying to win you over with a rewards program. Instead, they're building deep integrations, treasury products that are going to actually help you expand your runway, and innovative tools like an MC-based AI connector. Oh man, that's awesome. We can connect it to all of our agents into reporting and that will put you in command of your money as a twist listener you're going to get five hundred dollars cash bonus just for opening an account think of that you open an account boom there's five hundred dollars in it so leap on over to grasshopper.bank slash twist and use the promo code twist as a twist listener you're going to get a five hundred dollar cash bonus just for opening an account grasshopper.bank slash twist i'd love to see someone try and maybe that should have been the prototype. But for a decentralized network, BitTensor's launches back, say, a year ago were really opaque and had an information asymmetry where it was investors who were in the know who could decide whether or not a team got launched. And it was retail chasing after once the subnet had already gone to the protocol and was already pumping. So that was one big reason why we wanted to create a system whereby, hey, what if we could launch teams together in a distributed way and give retail the same chance as investors get, the same OTC style terms that you'd normally only get if you're an investor in return for crowdfunding a team to the protocol and getting them over that initial investment hump and building on BitTensor. Okay. So it's kind of community. It's kind of being a purpose-driven product in terms of does one thing very well. I guess my question is, how much money do you need to raise to put together a compelling subnet pitch pre-launch? And then is that raised in USD, a stable or tau? Right. Which is the BitTensor token, if you didn't know. Great question. So it's less about the amount as a fixed total. It's more about validation. And what I mean by that is, would this actually work on BitTensor? You might be an amazing ML engineer. You might be an incredible full stack dev, but BitTensor is different. It's adversarial. You're designing for a game theoretic AI environment and the miners are like very, very intense. They're going to tear you apart. So you might think you've got an amazing business idea and a great white paper, you've got the GitHub repo, but if you don't validate that it's going to work in a distributed adversarial system, then it's more like you could get wiped out and lose your initial capital, right? So yeah, go ahead, Alex. Well, the reason why I like this lawn is that it sets up a way to kind of screen out the crap and then therefore allows people to have more confidence in both backing new subnets, but also investing in the ones that have already made it. But here's the thing. It doesn't feel super decentralized to need bespoke on-ramps, if that makes sense. So tell me if I'm being overly precious here, but it does seem like when I talk to folks in the realm of BitTensor, we talk about community and kind of caring for the ecosystem, which is all well and good, but it sounds a bit more like a gardener pruning a tree than letting a forest grow wild. Well, I want to get Brian's take on this as well, but my take on it would be BitTensor, So Alex is absolutely right. It's meant to be that way. It's meant to be super competitive, right? But BitSense is also, as well as being hyper competitive, it's also extremely cooperative in that there's a lot of like cross-pollination. There's a lot of openness between the teams. There's a lot of collaboration there too, right? There's a lot of like shared resources. We go to the same conferences, people know each other, and it's the combination of the two. It's the integration of competition and collaboration that really succeeds. The thing that was getting me about launches was that because the funding to get the subnet slot was really concentrated in about maybe four different types of investors, a subnet slot can cost, say, a quarter of a million dollars, maybe more in Tau, and that's burnt now. So that's a sunk cost. So if you have to go to investors to say, hey, can you give me that initial startup capital? Their terms are often like, OK, we'll give it to you. We'll give you that initial 100K, but you have to give us 20% of emissions in perpetuity. And then suddenly you get like a small group of investors owning like 80% of the teams on the protocol. Hence, hey, what if we crowdfunded it? That way you don't have these investors who have to put up that first quarter of a mil. and the teams aren't weighed down by having to give away 20, 30% of their emissions forever, which means less to spend on the subnet. Yeah. That's an insane cut. There are only like 128, I believe, subnets in total. So how competitive is it for each of those slots? Is there like a long waiting list for like some company has to go out of business for you to take over the subnet? Like what is that marketplace like? Yeah, I mean, there definitely is a process of like submit deregistration. Right. So, you know, there needs to be there. Like people have been deregistered in the past. Sorry about that. People have been deregistered in the past. But really, when it comes down to it is that like, you know, the competitiveness comes down to like the price of actually registering a slot fluctuates. It's not a fixed cost. Right. It's this dynamic number that changes. Like if I register, OK, well, it's going to double the next time someone else wants to register. So there's like a market value to registering. And it becomes basically like, can you register something before somebody else at a certain amount of money? And if you need that amount of capital. Yeah. So it's a bit like the sports franchise model. Like there's a new NWSL team. They had to pay a $205 million fee to join a limited number of teams. So you're kind of buying, you know, the Boston basketball team equivalent slot as part of the Bitensor subnet group. Exactly. And some slots have more liquidity than others. So one of the first subnets, if you get, say, one of the first 20 or 40 subnets, it will probably have a lot more alpha in it than a subnet that was registered later. So Handshake 58, where you're on now, this is on subnet 58. This slot has a lot more alpha on it than, say, subnet 120. So that means more liquidity, which means more capital to spend up front on the things that you need. So there's also competition there. Why does it have more alpha? I thought alpha tokens were the subsidiary tokens on a per subnet basis that were used to incentivize the miners and validators. I didn't know that they varied in quantity based on subnet number. I feel like I'm missing something here. It's when they were registered, they start emitting alpha. So some of them got registered over a year ago. So they've emitted more in that time. They all have the same fixed total. There's always a new corner in the TensorFlow land for me to look around and go, I didn't know that. Can you imagine starting a subnet, Alex, and not knowing this stuff and then being like, wait, hold on a minute. I think there's some really strong intrinsic value to what Bitstarter is trying to do. So I primarily work at Macrocosmos. You guys have had Will and Stefan on here in the past. Great folks. And just learning how to go through the process of creating a subnet and doing everything from two years ago, when there was almost nobody in the ecosystem. And people knew, but there's a lot of tribal knowledge. Bitstarter was the very first really official initiative that was trying to give back to the community and say, okay, there's this whole treasure trove of information that you need. You need to go from zero to one really, really fast, and that's how you're going to be successful. Yeah, so you guys add credibility and guidance. But also, I feel like if a subnet goes through Bitstarter, given your guys' place inside the ecosystem, it's a really big stamp of approval. It's credibility, essentially, instantly. We try and bring together a mixture of experts of the best people on the protocol to give free discretionary advice to the applications that come in, the ones that pass our initial review. We help them build up their proposal. We then share it with a cross section of the ecosystem. People have run validators, miners. Jacob, the co-founder of BitTensor, is on the advisory panel. and it's through their advice and their commentary that helps improve the application if you're a subnet a prospective subnet owner you don't have to take their advice but it means that lots of senior people in the protocol have had a chance to help you if you want it and then even if not you get to pitch it live on air through our show so that you can find your people and at the beginning it can be really hard to get attention on your subnet like Lon said there are 128 of them So by starting out by you've got the best people in the protocol looking it over. You've got backing from people who've built it before to improve your proposal. And then you go live on air with a crowdfund behind you. We've gotten like up to 2000 people before. It was like the second most watched show on BitTensor after novelty search, which Jacob posts. So you get a chance to find your people, make your case and then hit the ground running. 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Try custom agents now at Notion.com slash twist. That's all lowercase letters. Notion.com slash TWIST. And when you use our link, you're supporting our show and keeping it free and vibrant. Notion.com slash twist. Have you noticed any, I mean, you've run a lot of these competitions now or a lot of these sort of projects. Are there certain kinds of projects or certain kinds of pitches that get everybody's attention and sort of do better naturally on the system. Like I know Kickstarter always worked that way. People were always like, oh, you got to put like a horror short. The horror does great over there. You know, that kind of stuff. Right? That's the exciting thing is that what are the parameters? What are the best startups for building on distributed systems? What does a community like BitTensor really respond to? What turns them on? And a lot of it actually comes down to the founders and the founding team. And there was a team we launched back in January. We did it live from Davos and no one had heard of them. They've been in stealth mode. They were two tenured professors from an East Coast university. And then the other one has a chair at Harvard in philosophy. And they also have an AI podcast and run a hedge fund. And they had a business already built and launched in the same sector that they were going to build the subnet in. And we completed their raise in under an hour. That was 600 tau. So when you have great founders, no one's heard of them. There's this element of surprise. We dial people in from different parts of BitTensor to give their perspective. That can be great. But long term, what you're looking for is what are the types of problems that are best solved on a distributed system? And what do they need to succeed when they hit the protocol? There's the liquidity pool management. There's the social media aspect. There are managing the miners and the validators. So it's a really complex entity. We're tracking every team we launch so we can learn as we go what really leads to success. It's a little bit like subnet university. It's a little bit like what he's doing for founders, but for people specifically in subnets. That's what it makes me think. But you know, if Jason gives you money, he gets stock in return. So I'm curious. Bitstarter as a project makes sense to me now. Really appreciate the explanation. Is it designed to be a revenue generating business or is it more a community arm of the BitTensor folks to help get people onto subnets that are being either misused or underused? We take 3% of emissions for the first 90 days. after they get to post-launch. That's a lot smaller than what a lot of other incubators take. But our mission was to build BitTensor better. I know that actually subnet owners only get 18% of total emissions because 41% goes to miners, 41% goes to validators. If you take more than that, right, what tends to happen is that they don't have as much disposable capital to spend on things like recruitment or infrastructure, which means that they tend to struggle a bit more when they get to mainnet. Whereas my gamble was, well, if we take less from them and we bring in more partners at the start, they can spend the money on the partnerships that will help them to thrive. They'll be less weighed down by someone taking passive income from them. Yeah. And I think there's also a big, big bet in there, too, right, where you're you're investing in them, taking less with with the hope that their alpha also appreciates. You want them to be successful. You want them to go through the whole process of creating something state-of-the-art, creating something that's going to change BitTensor or change technology in some way. Because then the relative value of that 3% is way higher. Yeah, yeah, yeah, yeah. But it's kind of staggering that people would want to take 20 or 30% of emissions in perpetuity and you're taking 3% for 90 days. is how do the economics work out on your end? Because that could be a smaller sum of money if those tokens don't appreciate greatly in the future. So are you willing to just kind of eat the work just for the sake of the networks overall? At the beginning, it was really important to prove that this works. No one ever tried this on BitTensor before. You're pledging tau for future alpha emissions. And we wanted to prove that it would work. The 90 days, 3% thing, it's perfectly viable. but it's harder to work with teams long-term. What happens when we've launched 12 teams or 20, right? Will we be able to work with each one long-term? So we actually are setting up a venture studio so that we can put up front more of the investment in launching a team and then be able to incubate and accelerate teams for much longer periods of time. And in fact, we actually have some news that we want to break right here on This Week in Startups with you guys. All right, we love breaking news. Look at that. Which I wanted it to be enough of a surprise I didn't even tell you guys beforehand like in the backstage. Fixed by the way. We heard nothing about this coming next. There's nothing like doing things live. So our second team that we launched, Subnet 24 Quasar, they do long context models and intelligence. That means that they're looking to expand context windows for LLMs. We launched them in January. Three months later, they're about to release their own model. And they're close to being in the top 10 subnets. They have a fully diluted value of about $84 million. And what they were doing impressed Jacob so much that he decided to back them himself. And that happened to another team that we launched as well. And so when we were talking to Jacob about it, Jacob said, I want you guys to help bring more machine learning research teams onto the protocol. And I want us to be able to build a fully decentralized tech stack for BitTensor, where where we bring in the top machine learning startups and research teams to build on the protocol. So Jacob has given us funding to register subnet slots for machine learning research teams in a new machine learning track on Bitstarter where we be working with teams across the protocol to deliver state across a number of benchmarks, working with teams like Macrocosmos, like Targon, who have already pushed the boundaries to bring in the best machine learning researchers, incubate them, and help them to succeed on BitTensor. So to help them succeed on BitTensor, though, implies that, Well, one, congratulations. Should have started with that. Thank you. But it implies that there's enough room for them. And one thing that I keep kind of looping back to is this hard cap of 128 subnet slots. I know it was 64 back in the day. But to get all these ML engineers that you're hoping to have into the ecosystem, to me, implies you're going to need more total parking spots. So is that something that's being discussed? Is that coming? Or is much like the 21 million Bitcoin cap, is 128 the end of it? It definitely isn't the end of it. It will expand. And when Jacob was on novelty search to talk about conviction, he said that it will, they're definitely going to expand it to 256 soon. I think when we went up to 128, the quality got a little bit uneven and was spreading out emissions over more subnets. There isn't really a hard limit. It's already a very, very large chain, BitTensor for a layer one, but it can handle more and it will go up again. subnets get deregistered right now every couple of weeks and other subnets are for sale so we've had a lot of new entrants in the past week alone we've had about three new subnets come in so the recycling is actually quite strong it's like what you were saying earlier alex it's really intense competition so with the deregistration we can get a new team in every month yeah it's okay there's a sustainably it's very hard to run a subnet like the the the process of trying to do everything from the marketing to the engineering to the socials to the to the organizing of your own company right like there's a lot of different components there so like it just naturally the churn is going to be high yeah so you know like institutions like or like microcosmos or or yeah like targon or the shoots or the the quasars of the world you know they've gone through that process and been able to be successful and again that's what you know um bitstarter is trying to do is to like pull out you out from the churn right but there is there's still a lot but yeah fundamentally like you should be able to go to like, you know, eventually it'll be to 256 and then it'll be 1028 and whatever that, whatever that comes to being. But there's definitely space within the ecosystem of BitTensor to have more machine learning. Like I think for me, for what I've seen in the past couple of years, there was like a few really good nuggets of ideas and research, LLMs. And then we went through this huge, massive product phase of like expanding the number of subnets and people trying to find product market fit and finding revenue and doing all these sorts of things. It almost feels in some way, shape or form, like the predominant energy feels like, okay, we need to do more machine learning. We need to do more of this stuff. And like, that doesn't necessarily mean that there won't be more products in the future of BitTensor, but there definitely is a lot of space, a growing space to do more like fundamental research, to do more collaborative research, to do more like fundamental things on BitTensor to like, you know, push the field of machine learning and artificial intelligence forward. Well, this answers the question that Lon and I had in our notes, which is, you know, how many more ideas are feasible for this adversarial decentralized model and it sounds like even inside of the very niche area of ml in particular because there are different projects out there uh tons of space left to build to to work and to host these competitions so lon i i guess you know maybe we're gonna end up with you know two five six subnets out there more more faster another time to make better stuff future twist episodes i'm happy to hear it yeah yeah i think i think also too just like putting a um another note in there right like i think the founders um jake and ala and particularly jake like they're very amenable to what the next generation is going to look like right so yeah something happens in the ecosystem and they want to make the right move as fast as they can right and sometimes that it goes well sometimes it goes poorly but i think like that gradient of improvement is really fast it's accelerating and if we find ourselves in a situation where like oh we have so much talent we don't have the space like that that day will come where we just we increase it yeah yeah um i I wanted to just touch on what people actually will get when they submit to the incubator if they're chosen, because we will register the subnet for them. So that's the upfront cost that several hundred Tau paid for. We also have a partnership with subnet for Targon, which is run by Manifold Labs. They're offering free compute to our incubated teams for their post-launch period. We're also in talks with Crucible Labs, which is run by Alla, who's the other co-founder of BitTensor with Jacob. exactly it's confidential compute targon just published a paper with intel they are about to launch targon os they have the targon virtual machine and by all accounts it's highly reliable which is what you need when you're doing say pre-training of a model um quasar already have a partnership with targon and it's helped them to train their models so we're creating a system whereby we've got a cross protocol selection of existing infrastructure that can help power the latest ML researchers to success. Long term for these other subnets, it's good for them commercially and it helps to create like a network effect of machine learning research on MidTensor. So there's several kind of like individual loops that improve things. As you make better models, you can bring those to bear another subnet competitions. Therefore, those will yield better results therefore bring in more people competition for emissions goes up tau becomes more valuable the ecosystem is worth more and then suddenly more people show up yeah it's a it's a great idea here's the thing that i want to flip around though jason's a huge bull we talk about it all the time on the show what's bit tensor's weakness like if you had to pick one the thing that keeps you up at night what's what's the other side of this of this coin with it with every technology that there's there's always there's always some weakness i think one of the things is it's very difficult to find the right project. I think it can be very difficult to parameterize your problem in the right way to get the actual most benefit out of it. It's kind of an art, and it takes a lot of time to figure out what that looks like. Sometimes you can find a problem where if you're not expressive enough, you won't be better than the version that you created because you've been the one thinking about this problem for many months, if not years, and then trying to launch it on BitTensor Or if you don't do that in the right way, you won't end up in a good place. Right. So, again, like places like Bitstarter are trying to circumvent this where, you know, you can talk to someone like myself or talk to someone else in the community and be like, oh, obviously that won't work and you can you can go further with this. Yeah. Do you have anything that you want to say, Chris? I think its biggest weakness is the same as its biggest strength. And it's captured in this phrase, which is if your system only works when people play by the rules, your system doesn't really work. bit tensor you have to design your product as if as if it's for the people exploiting it because you know that they're going to get you it's going to get exploited you have to think in this really unusual inverse way where you're like you have to design it with the exploit in mind so that it's almost like a jujitsu move whereby when people go to exploit you you use that power against them and it gets stronger right and thinking like that is very unusual we don't think like that in most of life because your miners are your users and normally you'd be like we got to do everything we can to make this as smooth and clean and enjoyable for them as possible but in this case it's like yeah but they're also trying to screw me and so i have to like navigate around that in advance yeah so so you're creating you're not launching a business or a startup you're launching a network right and actually networks are the more appropriate home for ai than a business which is limited, proprietary, closed bot. That's not where AI is eventually going to live. And the clue is in nature, right? Look at how intelligence develops in the natural world. It didn't develop in a single place. It developed through the survival of the fittest, natural selection in a distributed system of predator and prey. That's exactly how we're building intelligence on BitTensor, minor validator, right? You're creating, you're distributing the roles and you're creating the adversarial environment for that to grow. So it is the better home for it. It's just, if you thought running a startup was hard, try running a BitTensor subnet. Try running the process of evolution. Yeah, I was going to say, Darwinian evolution via natural selection, aka BitTensor. That's going to bring in all the founders, man. It sounds super easy. But if people do want to find out more about the program you just announced, apart from going to bitstarter.ai, your main site, where can they go to learn more? So we will be opening submissions next week. We have a submissions portal for that. We are going to be incubating three teams a quarter. So applications will open app.bitstarter.ai. You can also follow us on X. I'm at Macrazac, also at Bitstarter.ai. So we'll be announcing the eligibility process there. And we already have a couple of applications that we had beforehand that we put into the track. And we'll be publishing the guidelines as well. All right. Well, guys, we're super stoked about it. When you have your first three, come back on the show and tell us all about them because we're always here to learn more about awesome subnets. Thank you both so much for your time. And you can now turn off the Halloween light behind you. Thank you very much. Next up, we're going to bring Ning Ren up from Trajectory RL. Ning, welcome to the show. Yeah. Hi. I'm very happy to join the podcast. We're delighted to have you. We're absolutely stoked. So we're going to go from the macro picture of the BitTensor economy down to a single subnet. What we'd love to hear from you first is the pitch. What does Subnet 11 trajectory RL do? Yeah. Okay. Let me introduce myself a little bit. So I'm a founder and CEO at Trajectory RL. So Trajectory RL is a new company running on Bitensor. So if I put one sentence to describe the Trajectory RL, so it is a new type of software company. It's building software not for humans, but for AI agents. So nowadays we call them skills, but the future like we may come up with like a better name, but now like we are like running a company, continuously producing such skills on software for AI agents. But like I said, like now everybody's talking about like Cloud Code Hermes and you talk about co-workers, like everybody using it. So if you think about it, so we are in the middle and very early days of a paradigm of platform shift. Like those AI agents become the new computer platform, become the new smartphone, become the new operating system. Just like any other existing operating system before, like they really need software to power them up to be useful. Like now, like if you see around like there are some skill hubs like all around world, like people still writing skills by hand, like using and web code and tools. Like, yeah. But like we envision like future, most of those skills will be written not by him, but by AI agents. So this is the, yeah. For some people out there who are a little bit behind, a skill is a skill.md file. It's essentially plain text. It's the written word, not code. And it's essentially a set of instructions to help an AI model or agent do one thing in particular. Is that fair, Ning? Oh, yeah. So like, it's not necessarily be only a skilled MD. It can be a combination like a skill, like some like MD files, combine some Python file, like code examples. I can some like logic to tell the agent how to do some like a business in a domain. Yeah. Like it could be like your personal CRM. It could be a Twitter post, like a writing tool. It could be a website creating tool. Yeah. We've had a lot of these in our open clock conversations, for example. So we just had the folks on from Bitstarter talking about the economics of running a subnet. So tell us how Trajectory RL uses BitTensor to create and encourage the creation of better skills. If you think about this, it's very like an interesting problem, like how we can organize. So basically we use BitTensor to orchestrate like the agents all over the world to compete, to collaborate, to write a good skilled IMD or like a skill pack. I think the first challenge we have is to create a good benchmark tool. Because now if you see around there is no good way to measure how a skill is running on an agent. People just post, many people don't use. This is a very innovation we create. And so basically we create a sandbox. Technically we call it sandbox, but you can think of it as a puzzle box. Like the agent come, an agent can come, like Code Hermes can come and open the puzzle box. And there are some tools included in the box. And it just gives a puzzle to solve. Like we just compare, like compete. It's solving like the miner can write, using any technique to write a good skill, the MD, and the power agent, and to solve this puzzle. We just rank and score. But in this sandbox, though, each agent would have the same model and harness. So that way the individual skill file would shine versus something else influencing the performance. Basically same model, but like a different harness. So we compare across different harnesses. Like the harnesses. But we want basically know the skills, how it performs with different harnesses as well. Okay, so Lon is a writer and I'm a writer, which means that skill files make a lot of sense to us because when it comes to typing out words and sentences, that's our bag. But I'm curious if that inherent method of creating skills, these markdown files, these text files, gives them a lower ceiling in terms of improvement than if they were done with code. Or alternatively, does it create a higher ceiling for improvement because they are written in English, for example, versus in code? So I see there is a higher ceiling for the skills. So if you see, there is a theory called the fat skills thing harness. I could mean, so like people think that the harness, yeah, it's more like the operating system is only handle like the file reading and like talking to the different IAMs, like the input output. And there is a core component called Resolver to just decide at the right time to load the right MD file. And all this does like the harness doing this well. And the other, the rest, really magic happens and all the intelligence will happen in the skill layer, in the skill space. Like if you think it's like open, you can think like people will have their own CRM. Like it's a skill, like different people will have different CRM a little bit. And like eventually there will be like infinite kind of skills. I mean, I guess my question would be, I have a few skills that I've made and I'm not a coder, but just like, hey, help me with YouTube titles or whatever. And the way I make them is, you know, I sort of work on them with Claude together until we're happy with how the skill is written up. And then it's trial and error. I'm trying it. Oh, I forgot to tell it to capitalize or it's using too many M dashes or and we sort of vibe code the skill together for a few hours until it's like perfectly tight. So is that essentially the same process that your agents are now replicating? Or is it more of like thinking about it in advance and taking out the sort of vibe coding time waste period? It's kind of like a similar process, but just like nowadays, like you, like using right to the skills by hands. But we want to replace by using agents. Like we designed the mechanism, like mine are already using agents to write in scale.md this way. But they use agents, they also use the webconic tool, but they run their benchmark. Like they measure the result of the scale.md and they use the agents to iterate like you do. But they deliver, like they hand more and more work to the agent to automate this flow, this workflow. So this is what we want. I think I get this. The question then becomes, what skills are the most interesting to set up competitions for to improve? Because Lon just mentioned he's got this YouTube title skill. A bit niche, interesting, useful. A lot of people make YouTube videos. They all need titles, man. Maybe it's a good point. Is that the type of skill that is a good fit for Trajectory RL? or is it more general skills that are going to be the early product market fit use case? Good question. Good question. So there could be like a very different type of skills. And so we are still, we are also exploring like which one could like it's better to mirror. And so that's why we set up a season. Like the first few seasons, we want to explore some like meta skill. like it's easy to measure and it's more widely can be widely used like the self-learning skills that this is the first season so we just launched our first season for like less than a week and yeah i can so i can please can share i can show you yeah so you can see so there are like a different type of skill we can we can measure so like the first season we do like do some like a meta skills called self-learning. And we want to enable the agents can just when they encounter some errors they can learn and they can fix them themselves This is the first thing We just launched it for less than a week So you can see we create our benchmark. Yeah. Tell people what this chart shows, because a lot of folks are on the audio version. So tell them what they're seeing here. So basically we bring some popular self-learning skills because they are already on the skill hub like many other places. To run our benchmark and we also pick the winner in our subnet to do a side-by-side IPOs to IPOs comparison like how they work. Because we can mirror, we create a benchmark so we can improve. If you can not mirror, you cannot improve. So if you see the leader poll, like we only run for a week. We already see some very promising. Without like our subnets, we already performed a little bit better than the SOTA on the market. So just by keep running this season, we will get our very good SOTA self-learning skills. So to answer your question, to back to your question, yes. So we will compete on more and more different type of skills, but we will start from the meta, more like a general meta skills first. So we have companies in the world line building AI models, both open and closed source. We have BitTensor having several subnets that are working on training models in a decentralized basis, in an open basis. and now with trajectory we have a way to apply the same competitive logic to skills essentially turning each skill file or skill that you can use into an improving process similar to what we see elsewhere okay so the result of this ning is that everyone's agent is going to be more capable and more performant out of the box because the skills you can bring to them are already better okay That makes a lot of sense to me, and I would love that. I've made some skills, too. They're garbage. So I would love to get some help from the experts. Yeah, I think that leads to my next question, which is, I mean, conventionally, the way I think of skills, they're basically free. Like, somebody designs a skill, and then they tweet it out, and then they're like, hey, I wrote this X article about how I trained my new open claw skill, and da-da-da-da-da. Try it out yourself. Here it is. And so, I mean, I think you're sort of looking forward to a future where skills become a lot more dense and a lot more valuable. And then there also is money sort of they're actually worth something and people would pay you for a skill. Is that the vision? And how much do you think people are going to be willing to drop on a really amazing right out of the box skill? So I think in future, there definitely will be the business value inside and skills. So if you remind the early, like 90s, early PC days, there will be a bunch of free softwares. But later, like the smartphone, app store, but later there will be super software. There will be Instagram. So if you, like, our current mission is to maximize the distribution and installation of the skills. And later, like, there are hundreds of ways that you can figure out to the, like, monetization. tination. And do you need to monetize the learning? Because the way that I was thinking about the competition, the BitTensor subnet kind of self-funds via emissions. So could you create a system here that doesn't actually need to have a business on the backend? And instead, it's essentially just a recurring competition to create better and better skills. And then everyone can use them because, you know, Tau emissions filtering down to the subnet compensate everyone for the work they're doing already? Yeah, good question. So this is actually exactly what we are doing now. So we are leveraging the Bitensor incentives to drive the agents to submit, to optimize the skilled MD. But my thought would be, in the end of the day, we still need to find the PMF. We still need to make money, make a real product. And so we just like take advantage or we just take benefit from the Bitensor to like a co-start us, like we incorporate us to a state like we have like a super massive adoption and we can like find a way to charge to user, to like user pay. Or there's also another very good angle, like the trajectory of the data. So when we run so many skills and collect so many data, those data are also valuable as well. So we can sell this to the model. We can even try and like find our models to like, yeah. I got one more. I got one more question. We'll let you go, Nick. What is the most valuable or useful skill that's been designed so far on trajectory? Can you walk us through? I want to get a clearer example of how intense and awesome these skills are going to be. Oh, okay. Yeah, so since we just, we are relatively new, We are like about more than one month on BitTensor, which launched our first season about less than one week. And the first thing about self-learning, so we all already see good self-learning skills. Like just about one week is very impressive. So people already find some good way to write self-learning skills at IMD. So now you can go to our website and try those skills, self-learning skills, to just make your agent. So if you use them day-to-day, make them make less mistakes and save your tokens, solve a problem more effectively. All right. Well, we really, really appreciate it, Ning. What's the website? And tell us when Season 2 begins. Oh, Season 2. So the website is trajectoryrl.com. trajectoryrl.com. Yeah. So the season two will be held in about one month. So we plan to hold the season one for one month and the season two start after that. But in the future, as I said, we want to drive this process all by agents. And we want to continuously roll up new seasons just by agents. We want to build an AI native company ourselves. Well, I freaking love it because I need better skills. I think everyone does. And I think that this is such a lightweight, easy to share format that if you make a better one, the whole world gets to benefit from it. So to me, there's a lot of really like human positive gains to be had here. And that's just super encouraging, Nick. And thank you. Thank you, guys. All right. Well, Nick, thanks for coming on the show. After season two, come back and tell us what people have built and tell us how much you're improving the world because I want to stop working very soon. So I'm hoping that AI gets me there. Thanks, man. Appreciate it. Thank you. I like thinking about companies in terms of season. You get to talk about it. It's like TV. Like, man, I can't wait for season two of trajectory RL. They're going to really up the stakes. I mean, the thing that really blows me away here, Lon, is the simple fact that we're now seeing essentially a decentralized network designed for ML competitions coming together to have the nerds battle it out to write the best sentences in English. Yeah. And it's funny that skills are just marked out. I did not even realize that when I was first teaching them OpenClaw. I thought it was writing code in there. It was like, hey, Claw, here's what I want you to do. First do this. Like, oh, I could have done this myself. I remember when Anthropic first announced these. I was reading through the announcement. This is back in, like, what, mid-25, late 24, somewhere in there? Sure. And they were like, a skill.mg file is a text file with words in it. And I'm like, what am I missing here? This sounds useless. Why would you ever want that? That doesn't do anything. And then it turns out that, one, they were right and it was wrong, but also the power of the written word. I think that a lot of the power of open claw initially to doofuses like me, like I'm sure the coders got it immediately, like why it was valuable. But it was just that. It was finally delivering on the, you can literally just tell the AI what you want and it'll just do it. Like we've been promised that for so long. And then you would use open claw and you would just be in your Slack and you'd be like, do this. And it'd go, okay. It wouldn't always work, but it would say, okay. Yeah. And it would like act like it understood you. You know what might be a good model? We should have kept Ning on for this, but whatever. I'll just say it now. before we move on. Have you heard of the humble bundle model? Yeah, the gaming, like Valve games. If you buy them, you get a bunch of indie games for one low, low price, and then you can try them all out. Yeah, you can get like, you know, 15, 20 games for like 10 bucks. And so to me, like, I love to contribute to projects that I enjoy, things that I really love to use. If you're a metal band that I follow, I own several heavy metal Christmas tree ornaments, not because I really need them, but because I wanted to support the bands, you know? So if they did a humble bundle of skills, I would so happily contribute to paying 15, 20, or even like a hundred bucks, frankly. I do, I will say, I notice how much my skills get better over time as I iterate. Like every time I notice something I don't like, I go back and fix the skill to like, make sure that doesn't happen again and vice versa. And so if that, if doofus me who's barely paying attention can bring that kind of iteration over time i can only imagine that people who were really focused on and incentivized to make these skills much better they could be a hundred x better i'm only making it or three x better because i got other you know one you got to stop you got to stop with the putting yourself down you're oh i'm a doofus oh i'm not a coder you have been deep in the open claw trenches to the point in which i know the name of your agent which is a weird thing to know it feels a little bit too personal it's like the The everyday villain's character for Blade Runner. But you use Open Claw a lot. You use AI all the time. You know, I don't. You've made your own skills. I did use Open Claw, but my Open Claw is locked in an AWS rack somewhere, and he has a lot of trouble getting out. Like, people are very dubious about a bot that's inside AWS. They're like, get out of here, you. So I actually have switched. I'm mostly using Claude Cowork now because it's much easier to just, you're just like, here, take, you're in my notion now. And Claude goes, okay. and Gaff is like, I can't get him. What are you trying to show me? Can you copy and paste the whole thing? But the same skill and defile works on both, which is incredible. It is incredible. That's the power of them. All right, before we go, a couple of other things to note, folks. From the news tickers out there, AngelList just dropped right before we got on air a new product called USVC, which is a private market fund designed to give individuals who have $500, which is the minimum, exposure long to a number of major names in the world of venture capital startups. Yeah, I love that you said you could just have $500 as an exclusive group. No, I mean, that's the whole point. It's not. I mean, everyone has, well, I'm not going to say that and get made fun of on the internet, but most people can find $500 somewhere and then they can take part in venture economics. I got to read a little bit of the prospectus and what I learned is this actually operates a bit like a venture fund. You put money in, you can't take it out. Right. There will be some repurchases on a quarterly basis, but mostly you're waiting for exits. Yeah. I see they have here on the website, the power law. One investment has the potential to generate a higher return than the rest of their portfolio combined. This is why USVC intends to build a bundle, not a single bet. So the idea is even your 500, it's getting spread out so you're not all in on one thing and then you lose your shirt. Yes. Yeah. I think it's a great idea. We'll have more about it. This is actually one of two products. Robinhood has a publicly traded venture-y fund thing. So this does seem to be a growing product category as companies stay private. I did notice with the Robinhood one, they're kind of locked out of a lot of the most sought after private companies. I wonder if that's going to happen with this as about like open AI. They're not exposed to open AI and the Robinhood Venture Fund. And a lot of people were like, why not? That's what I want. Do you know where a lot of venture capital funds run their technology? AngelList. Do you know what that means? AngelList has a lot of access to that. There you go. So I'm hoping that this is actually magic, frankly, Lon. My expectation is high. Your expectation is magic. I'm sorry. High expectations are a gift. They're welcome. Next up, the Compute Wars. continued to absolutely go crazy. Two things of note here for everyone out there paying attention. Lon, first of all, Anthropic and Amazon pinned a new deal this week. $5 billion of investment, 5 gigawatts of compute, $100 billion worth of spend over the next 10 years, Anthropic to AWS. And maybe, maybe this will solve the Claude crisis in which everyone gets locked out after 10 minutes? Theoretically. I mean, I think eventually Anthropic's got to be worried about how people will eventually solve it, which is find another model to you. I feel like they have a limited window here to solve this problem before people are like, ah, okay, I'll try codex. You know, like it's, the gap is closing. And we're talking about AI timeframes. So whatever you were thinking, divide it by 10. Yeah, exactly. You know, it's brutal. The other thing, and this came out today, is that Google has two new chips. They make tensor processing units. Don't forget, a scalar is a zero-dimensional vector. Sorry, zero-dimensional tensor. A vector is a one-dimensional tensor. Tensors have multiple dimensions. Anyways, it matters if you care about data shape versus flatness, but their TPUs are now on generation eight, and they have two different versions along, one built for training. Yes. Get this, TPU-8T, and then there's TPU-8I, which is for inference. I think this is brilliant, and I think it goes to show that NVIDIA is not going to make all the money in the world. Yeah, there's going to be. I mean, we're seeing there's so many of these companies now that are working on their own. Isn't there? There's Trainium. Amazon has Trainium. Yep. they should really work on the name for? Because it's just, it's like. Yeah, it's not, it's inferencing. It's like, it sounds like a mineral. Unobtainium from Avatar. Like we'll go one level deeper on that guy. We'll go, we'll go get the pickaxe out and figure out what's going on. There's also a lot of companies in the startup world. Etched is working on a LLM, sorry, a Transformer specific ASIC. Right. For example. Cerebris has those like massive room size chips they're working on. Wafer. And they refiled to go public last Friday. Oh, wow. It's a very interesting return to the markets. And then I guess, Lon, just one last thing before we go. Should we just talk for a moment about Apple getting a new CEO? Yeah, Tim Apple is out. John Apple is in. I'm insisting. Can we call him Johnny Applesey? We have to call the new guy. His name is John Ternus, but I think we should just switch over to calling him John Apple now. I think whoever's the CEO of Apple, that becomes your last name. I think that's only fair. Explain why you're saying this. Donald Trump messed up one time and called Tim Cook, Tim Apple. And it's I literally am not even here to make fun of our president. I just think it's a very funny thing to call the CEO of Apple, Tim Apple or John Apple. So anyway, yes, Apple CEO, Tim Cook. He's stepping down as executive. He's up again as CEO and he's going to transition to being executive chairman of Apple's board of directors. John Ternus, now John Apple, the current senior vice president of hardware engineering. He's stepping into the CEO role. I know that a lot of people were very excited that it's a hardware guy. And a lot of people are thinking this is going to represent, you know, rather than somebody who's sort of trying to, like, squeeze as much money as they can out of the job's legacy by releasing, you know, these new versions of the classic product lineup. Here's a guy that's going to, like, rethink the whole company based on, you know, silicon and new devices and where they are right now. Also, someone with incredibly deep DNA in the world of Apple. I went to his LinkedIn and I pulled this image. went to school at UPenn, 93 to 97, had four years as an engineer at virtual research. And then since July of 2001, he's been in Apple, which is nearly 25 years. And that's an impressive run at one company. And just goes to show that in the old days, you could work for one company. Yeah. For a while. You didn't get laid off all the time. I read that he was one of the lead sort of minds behind your new MacBook, your MacBook Neo. He was one of the champions of that, which has been a well-regarded sort of a rare new Apple product that people like and feel good about. So there you go. It's magic. It's magic because it's the first Apple product I've ever owned that if I drop a Dr. Pepper onto it and completely ruin it, I don't have to cry. I feel like I could- That's very free. I feel like I could drop a Dr. Pepper on my iPhone and it would stand up to that. I don't- Oh, I meant something with a keyboard attached to it. Oh, okay. Yes, yes. Fair enough, yes. Wait. If I torch my N3 Max Pro Viper, I'll be sad. I know we're wrapping up. I need to stop you right there. So what about the MacBook Neo? If you poured a Dr. Pepper on it, how would it be fine? I don't understand. Oh, I don't care. It's cheap. Oh, it's so cheap. I understand. Okay. I thought you were saying something about it, like a new kind of aluminum that repets Dr. Pepper? No, no, no. No, my pink MacBook Neo does not have special anti-soda properties to it. No, you're just saying you could afford to buy another one because they're not the most expensive thing in the world. I paid like $600 for it, which for a laptop. Yeah, no, that's really nice. Usually means you're getting some piece from HP, right? That's plastic and terrible and has gunk all over it. This is the infamous company that there's that video of Ternus on stage introducing the $1,000 computer stand. So your new MacBook costs less than that stand. Yes. Well, there is two markets for Apple products. There's sane people and insane people. And you know what? They sell to all types. One quick note here from our producer, Salah, who says that Dr. Pepper tastes like medicine. Salah, you're fired. I love Dr. Pepper. And with that, Twist will be back on Friday. We'll see you guys then. Lawn and absolute treats. We appreciate everyone tuning in to the live show, The Noti Gang. We're back on Friday, noon, Texas time, 1 p.m. Eastern. Y'all are lovely. See you then. Bye-bye.